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光学相干断层扫描在上消化道早癌诊断中的应用进展

Advances in application of optical coherence tomography in diagnosis of upper gastrointestinal tract early cancer
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摘要 食管癌、胃癌是常见的上消化道恶性肿瘤。中国作为食管癌、胃癌的高发国家,大部分患者确诊时已是进展期,其5年生存率不到20%。若能实现上消化道肿瘤的早诊、早治,其5年生存率将超过90%,可以明显改善患者的预后。光学相干断层扫描(OCT)是一种无创、高分辨率、非侵入性光学成像技术,可以提供毫米量级深度、微米量级分辨率的生物组织微解剖图像。一方面可用于快速、无创地检测病变组织、器官、血管或腺体,另一方面还可以识别肿瘤早期病变的光学特征,对于上消化道肿瘤的早期诊断具有重要意义。该文综述了OCT的原理、分类,总结OCT在上消化道早癌中的最新应用进展,并探讨OCT结合人工智能(AI)技术进行深度学习的潜力。 Oesophageal cancer and gastric cancer are the most common malignant tumors of the upper gastrointestinal tract.As a country with a high incidence of oesophageal cancer and gastric cancer,most patients are already in the progressive stage when diagnosed,and their 5-year survival rate is less than 20%.If early diagnosis and early treatment of upper digestive tract tumors can be achieved,the 5-year survival rate will exceed 90%,which can significantly improve the prognosis of the patients.Optical coherence tomography(OCT)is a non-traumatic,high-resolution,non-invasive optical imaging technique that provides microanatomical images of biological tissues at millimetre depth and micron resolution.On the one hand,it can be used for rapidly and non-invasively detecting the tissues,organs,blood vessels or glands in lesions.On the other hand,it can also identify the optical features of early tumor lesions,which has an important significance in the early diagnosis of upper gastrointestinal tract tumor.This paper reviewed the principle and classification of OCT,summarizes the latest application progress of OCT in upper gastrointestinal early cancer,and discussed the potential of OCT combined with artificial intelligence technology in deep learning.
作者 李俊杰 窦维佳 王新 LI Junjie;DOU Weijia;WANG Xin(Department of Gastroenterology,Second Affiliated Hospital of Air Force Military Medical University,Xi’an,Shaanxi 710038,China)
出处 《重庆医学》 CAS 2024年第18期2847-2853,2859,共8页 Chongqing Medical Journal
基金 陕西省重点研发计划项目(2021SF-182) 空军军医大学临床研究资助计划项目(2022LC2231)。
关键词 光学相干断层扫描 上消化道早癌 人工智能 综述 optical coherence tomography upper gastrointestinal tract early cancer artificial intelligence review
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